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Blended Learning course Full-time course Part-time course
Higher Diploma in Science in Data Analytics for Business

Springboard

Springboard+ is co-funded by the Government of Ireland and the European Social Fund as part of the ESF programme for Employability, Inclusion and Learning 2014-2020.

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Higher Diploma in Data Analytics for Business Course Overview*

The Higher Diploma in Science in Data Analytics for Business aims to provide an opportunity for learners with a degree outside the computing arena as well as those currently involved within the IT sphere to refocus and reskill for careers that require Data Analytics knowledge and skills. The programme is designed for graduates of any discipline with competence in IT evidenced through qualifications or experience, particularly those already working in or aspiring to work as a data analyst. They will have the opportunity to continue to develop knowledge, skill and competence to remain competitive and employable in an ever-advancing sector.

Data Analytics is among a set of emerging and rapidly developing technologies termed Innovation Accelerators, which have been identified as being critical to the next wave of digitalisation.  According to Gartner’s Hype Cycle 2019, over the next decade, data analytics and AI will augment workers’ efficiency, as companies rely on leading tech to beat out competitors.

This Higher Diploma in Data Analytics for Business is a rigorous and highly skills focused conversion course, dealing with current business trends in the use of big data and the tools and technologies used in implementing data analytics across a wide selection of business types undergoing digital transformation. . The design and development of modules within this programme was informed by significant industry consultation, particularly from Microsoft and its partner network. The course deals with the different types of statistical analysis and its underlying implementation.

For September 2020, this course will be 90% funded for eligible applicants on a part-time basis through the Springboard+ ICT Skills Conversion Courses initiative.  The course will also be offered on a full-time basis through the HCI Pillar 1 courses funding (Human Capital Initiative). 90% of the course fees for the full-time programme will be covered for those eligible already in employment and also to 2020 Level 8 Degree Graduates who are academically eligible for admission and wish to specialise in Data Analytics. The full-time programme will be offered free of charge to those eligible applicants who are unemployed, formerly self-employed and ‘Returners’.

*Subject to validation.

Read more about this Graduate Higher Diploma in Data Analytics for Business below:

Students will undertake learning in the subjects of programming, mathematical, logical and strategic thinking as well as machine learning, data gathering, analysis and visualisation and the subsequent business application of these skills. Industry-initiated real-world problems will be provided by our industry contacts and used as the context for planning and designing assessment solutions, as well as being an aid for problem-solving sessions.

In addition to the data analysis and associated technical skills, which will be fostered during the participants studies, transferable skills that will be developed throughout the programme via the varied teaching and assessment methods include: critical analysis, advanced evaluation, self-analysis and personal reflection, problem solving, communication skills, team management and group-work and professionalism.  The programme is underpinned by a Strategic Thinking Capstone module which spans all semesters and is assessed by a Problem Based Learning (PBL) project. The module explores current strategic thinking issues companies face today, such as data protection and privacy and the challenges and opportunities of emerging technology.

  • Strategic Thinking
  • Statistical Techniques for Data Analysis
  • Data Preparation
  • Machine Learning Principles for Big Data
  • Data Visualisation Techniques
  • Machine Learning for Business

As this is a blended learning programme students will be required to engage in a combination of on campus and online activities. All students will be introduced to the CCT online learning environment as part of the induction to the programme and will have access to further support as required.

Online activities can include live or pre-recorded lectures, independent learning and assessment activities such as research tasks, discussion forums, simulations, quizzes and e-portfolio work along with online group activities such as live classes, group project work, virtual labs and tutorials. Completing the online elements of the programme each week is essential to successfully complete the programme.

On campus activities can include small group tutorials, labs, project supervision, problem solving case studies, library research and seminars.

Learners submitting an application to the proposed programme should provide supporting documentation for application consideration, in line with any one of the below Access arrangements or minimum entry requirements:

The direct entry route to this programme requires applicants to evidence discipline specific expertise, including mathematical proficiency to a minimum of NFQ level 7. The following are accepted as appropriate evidence for direct entry:

a. An NFQ Level 7 degree, or higher, in a related discipline to ICT,
or
b. A level 7 degree, or higher, in a non-related discipline in addition to evidence of proficiency in mathematical foundations and techniques

This programme is designed for individuals who have previous knowledge in computing, or similar disciplines, through professional experience and/or educational qualifications. This programme is not suitable for individuals with only basic computer literacy. Learners must demonstrate proficiency in mathematical foundations and techniques (level 7 standard).

All applicants are required to have access to the internet and a laptop or desktop PC for the completion of this programme.

Applications of the basis of experiential learning or informal / non-formal learning must evidence an applicant’s potential to succeed through demonstration of ability to pursue the programme at the applicable NFQ level and benefit from the programme of study in question. The ability to produce written summaries, discussions and projects on academic and applied matters will be important.

Evidence may be provided through:

  • Prior study and qualifications, including CPD, short courses and professional awards as well as NFQ awards
  • Work experience and achievements
  • Other experiential learning obtained through volunteering or non-employment experience
  • Successful completion of an entry assessment set by the College
  • A combination of the above

There is no compulsory access interview. However, CCT reserves the right to request an applicant to attend a semi-structured interview in order to more fully establish the applicant’s suitability for the programme, their motivation and potential to succeed. This process can also be used to allow applicants to fulfil the requirement of competency in the use of IT.

There is no specified minimum experiential requirement for standard applicants. RPL applications are considered on a case-by-case basis under the CCT RPL policy.

Applicants whose first language is not English, must present English Language proficiency level evidence. English language competency required for entry must be equal to or greater than B2+ in the CERFL. English language credentials endorsed by other systems (viz. IELTS, TOEFL, Cambridge etc.) will be assessed to ensure they meet this minimum standard.

All applications for admission onto this programme should include:

  • Updated CV
  • ID Verification (passport picture page copy)
  • Attested original copies of degree qualification parchment
  • Attested original copies of final degree transcript of results
  • RPEL documentation as required by CCT
  • Evidence of English Language proficiency scores if the applicant’s first language is not English (IELTS, TOEFL etc.)

Those who are in employment/working : 

For eligible applicants who are currently in employment/working 90% of the tuition fees (for the part-time course or the full-time course) will be covered by the HEA through Springboard+ or the Human Capital Initiative (HCI) and the remaining 10% is payable by the student or their employer.

  • The Full-time Course Tuition Fee is €7,100 so €710 euro is payable by the student or their employer
  • The Part-time Course Tuition Fee is €3,550 per year, (ie €7,100 over two years) so €710 euro is payable by the student or their employer

 

Recent Graduates:

2020 Graduates who will have successfully completed a relevant level 8 Degree programme before September will be eligible to apply for the full-time course. 90% of the tuition fees for the full-time course will be covered by the HEA through the Human Capital Initiative (HCI) Pillar 1 and the remaining 10% is payable by the student or their employer.

  • The Full-time Course Tuition Fee is €7,100 so €710 euro is payable by the student

 

Those who are unemployed, formerly self-employed and ‘Returners’:

The full-time course is free for eligible applicants who are unemployed, formerly self-employed or who are classified by Springboard+ as ‘Returners’ or ‘Homemakers’.

 

All QQI accredited programmes of education and training of 3 months or longer duration are covered by arrangements under section 65 (4) of the Qualifications and Quality Assurance (Education and Training) Act 2012 whereby, in the event of the provider ceasing to provide the programme for any reason, enrolled learners may transfer to a similar programme at another provider, or, in the event that this is not practicable, the fees most recently paid will be refunded.

Ready to start your journey?